{"id":"W3126823409","doi":"10.1177/0020702020985227","title":"Building a better global health security early-warning system post-COVID: The view from Canada","year":2021,"lang":"en","type":"article","venue":"International Journal Canada s Journal of Global Policy Analysis","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for International Governance Innovation","funders":"","keywords":"Outbreak; Pandemic; Warning system; Public health; Global health; China; International Health Regulations; Middle East respiratory syndrome; Economic growth; Political science; Coronavirus disease 2019 (COVID-19); Development economics; Infectious disease (medical specialty); Disease; Medicine; Economics; Virology; Telecommunications; Engineering; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001032477,0.0003228006,0.001041673,0.0001766301,0.0003135638,0.0003159443,0.001013528,0.0000669718,0.0002401815],"category_scores_gemma":[0.001437256,0.0002457477,0.0007127665,0.001608148,0.00006308631,0.0002632677,0.0001922849,0.0007364532,0.000001874348],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.01899362,"about_ca_system_score_gemma":0.0461789,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9947416,"about_ca_topic_score_gemma":0.9971465,"domain_scores_codex":[0.993444,0.0007402074,0.001609706,0.0003103235,0.003327227,0.000568534],"domain_scores_gemma":[0.9932188,0.0002138963,0.001846071,0.000397045,0.003063007,0.001261117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001152293,0.0002326564,0.6675951,0.000129076,0.04829081,0.04145852,0.0002046611,0.005385138,0.00008831749,0.001723864,0.2125025,0.021237],"study_design_scores_gemma":[0.002794762,0.0001371959,0.7786304,0.0008946543,0.003516002,0.01886494,0.001252643,0.00118223,0.00003811244,0.001176054,0.1909952,0.0005178179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7614715,0.007046312,0.001912476,0.2226374,0.001663006,0.00008732342,0.004884638,0.00001411488,0.0002832833],"genre_scores_gemma":[0.9656306,0.0001639736,0.0005560529,0.03105822,0.00247054,0.000001007355,0.00009424178,0.00001415171,0.00001124933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2041591,"threshold_uncertainty_score":0.9999995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006791572982625426,"score_gpt":0.3140180281553917,"score_spread":0.3072264551727663,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}